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<div class="header">
  <div class="headertitle"><div class="title">ConvolutionFilter.cs</div></div>
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<div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">/*</span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="comment">    VectSharp - A light library for C# vector graphics.</span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="comment">    Copyright (C) 2020-2022 Giorgio Bianchini</span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span><span class="comment"></span> </div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment">    This program is free software: you can redistribute it and/or modify</span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="comment">    it under the terms of the GNU Lesser General Public License as published by</span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span><span class="comment">    the Free Software Foundation, version 3.</span></div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment"></span> </div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="comment">    This program is distributed in the hope that it will be useful,</span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="comment">    but WITHOUT ANY WARRANTY; without even the implied warranty of</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span><span class="comment">    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the</span></div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="comment">    GNU Lesser General Public License for more details.</span></div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="comment"></span> </div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span><span class="comment">    You should have received a copy of the GNU Lesser General Public License</span></div>
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno">   15</span><span class="comment">    along with this program. If not, see &lt;https://www.gnu.org/licenses/&gt;.</span></div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span><span class="comment">*/</span></div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span> </div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span><span class="keyword">using </span>System;</div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span><span class="keyword">using </span>System.Diagnostics.Contracts;</div>
<div class="line"><a id="l00020" name="l00020"></a><span class="lineno">   20</span><span class="keyword">using </span>System.Threading.Tasks;</div>
<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span> </div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span><span class="keyword">namespace </span><a class="code hl_namespace" href="namespace_vect_sharp_1_1_filters.html">VectSharp.Filters</a></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span>{<span class="comment"></span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span><span class="comment">    /// &lt;summary&gt;</span></div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span><span class="comment">    /// Represents a filter that applies a matrix convolution to the image.</span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span><span class="comment">    /// &lt;/summary&gt;</span></div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno"><a class="line" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html">   27</a></span><span class="comment"></span>    <span class="keyword">public</span> <span class="keyword">class </span><a class="code hl_class" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html">ConvolutionFilter</a> : <a class="code hl_interface" href="interface_vect_sharp_1_1_filters_1_1_i_location_invariant_filter.html">ILocationInvariantFilter</a></div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span>    {<span class="comment"></span></div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span><span class="comment">        /// &lt;inheritdoc/&gt;</span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno"><a class="line" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a32d973bf7389f4ac07d68ca9cf2a4dbc">   30</a></span><span class="comment"></span>        <span class="keyword">public</span> <a class="code hl_struct" href="struct_vect_sharp_1_1_point.html">Point</a> <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a32d973bf7389f4ac07d68ca9cf2a4dbc">TopLeftMargin</a> { <span class="keyword">get</span>; <span class="keyword">protected</span> <span class="keyword">set</span>; }<span class="comment"></span></div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span><span class="comment">        /// &lt;inheritdoc/&gt;</span></div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno"><a class="line" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#ade808cf103a8c230dfa7d04440853b2b">   32</a></span><span class="comment"></span>        <span class="keyword">public</span> <a class="code hl_struct" href="struct_vect_sharp_1_1_point.html">Point</a> <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#ade808cf103a8c230dfa7d04440853b2b">BottomRightMargin</a> { <span class="keyword">get</span>; <span class="keyword">protected</span> <span class="keyword">set</span>; }</div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span><span class="comment"></span> </div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span><span class="comment">        /// &lt;summary&gt;</span></div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span><span class="comment">        /// The kernel of the &lt;see cref=&quot;ConvolutionFilter&quot;/&gt;. The dimensions of this matrix should all be odd numbers. The larger the kernel, the worse the performance.</span></div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span><span class="comment">        /// &lt;/summary&gt;</span></div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno"><a class="line" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">   37</a></span><span class="comment"></span>        <span class="keyword">public</span> <span class="keyword">virtual</span> <span class="keywordtype">double</span>[,] <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a> { <span class="keyword">get</span>; <span class="keyword">protected</span> <span class="keyword">set</span>; }</div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span><span class="comment"></span> </div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span><span class="comment">        /// &lt;summary&gt;</span></div>
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno">   40</span><span class="comment">        /// The normalisation value that is applies to the kernel.</span></div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span><span class="comment">        /// &lt;/summary&gt;</span></div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno"><a class="line" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a4f2be240a6de3ec430e6b47cb22c3a31">   42</a></span><span class="comment"></span>        <span class="keyword">public</span> <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a4f2be240a6de3ec430e6b47cb22c3a31">Normalisation</a> { <span class="keyword">get</span>; <span class="keyword">protected</span> <span class="keyword">set</span>; } = 1;</div>
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno">   43</span><span class="comment"></span> </div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span><span class="comment">        /// &lt;summary&gt;</span></div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span><span class="comment">        /// The bias value that is added to every colour component when the filter is applied.</span></div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span><span class="comment">        /// &lt;/summary&gt;</span></div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno"><a class="line" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a8c83462414bf7df2ae2d2a957dbfbfc8">   47</a></span><span class="comment"></span>        <span class="keyword">public</span> <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a8c83462414bf7df2ae2d2a957dbfbfc8">Bias</a> { <span class="keyword">get</span>; <span class="keyword">protected</span> <span class="keyword">set</span>; } = 0;</div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno">   48</span><span class="comment"></span> </div>
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno">   49</span><span class="comment">        /// &lt;summary&gt;</span></div>
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno">   50</span><span class="comment">        /// The scale relating the size of the kernel to graphics units.</span></div>
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno">   51</span><span class="comment">        /// &lt;/summary&gt;</span></div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno"><a class="line" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a8328d79387cab9e761d82eb5b63425db">   52</a></span><span class="comment"></span>        <span class="keyword">public</span> <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a8328d79387cab9e761d82eb5b63425db">Scale</a> { <span class="keyword">get</span>; <span class="keyword">protected</span> <span class="keyword">set</span>; }</div>
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno">   53</span><span class="comment"></span> </div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno">   54</span><span class="comment">        /// &lt;summary&gt;</span></div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno">   55</span><span class="comment">        /// If this is &lt;see langword=&quot;true&quot;/&gt;, the alpha value of the input pixels is preserved. Otherwise, the alpha channel is subject to the same convolution process as the other colour components.</span></div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno">   56</span><span class="comment">        /// &lt;/summary&gt;</span></div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno"><a class="line" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#ab32f045d8dfdef1dd0dc1647ef4eac99">   57</a></span><span class="comment"></span>        <span class="keyword">public</span> <span class="keyword">virtual</span> <span class="keywordtype">bool</span> <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#ab32f045d8dfdef1dd0dc1647ef4eac99">PreserveAlpha</a> { <span class="keyword">get</span>; <span class="keyword">protected</span> <span class="keyword">set</span>; } = <span class="keyword">true</span>;</div>
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno">   58</span><span class="comment"></span> </div>
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno">   59</span><span class="comment">        /// &lt;summary&gt;</span></div>
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno">   60</span><span class="comment">        /// Creates a new &lt;see cref=&quot;ConvolutionFilter&quot;/&gt; with the specified parameters.</span></div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span><span class="comment">        /// &lt;/summary&gt;</span></div>
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno">   62</span><span class="comment">        /// &lt;param name=&quot;kernel&quot;&gt;The kernel of the &lt;see cref=&quot;ConvolutionFilter&quot;/&gt;. The dimensions of this matrix should all be odd numbers. The larger the kernel, the worse the performance.&lt;/param&gt;</span></div>
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno">   63</span><span class="comment">        /// &lt;param name=&quot;scale&quot;&gt;The scale relating the size of the kernel to graphics units.&lt;/param&gt;</span></div>
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno">   64</span><span class="comment">        /// &lt;param name=&quot;preserveAlpha&quot;&gt;If this is &lt;see langword=&quot;true&quot;/&gt;, the alpha value of the input pixels is preserved. Otherwise, the alpha channel is subject to the same convolution process as the other colour components.&lt;/param&gt;</span></div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno">   65</span><span class="comment">        /// &lt;param name=&quot;normalisation&quot;&gt;The normalisation value that is applies to the kernel.&lt;/param&gt;</span></div>
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno">   66</span><span class="comment">        /// &lt;param name=&quot;bias&quot;&gt;The bias value that is added to every colour component when the filter is applied.&lt;/param&gt;</span></div>
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno">   67</span><span class="comment">        /// &lt;exception cref=&quot;ArgumentException&quot;&gt;This exception is thrown when the kernel dimensions are not odd numbers.&lt;/exception&gt;</span></div>
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno"><a class="line" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a73b327812cc43052706a859db30ad9cd">   68</a></span><span class="comment"></span>        <span class="keyword">public</span> <a class="code hl_function" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a73b327812cc43052706a859db30ad9cd">ConvolutionFilter</a>(<span class="keywordtype">double</span>[,] kernel, <span class="keywordtype">double</span> scale, <span class="keywordtype">bool</span> preserveAlpha = <span class="keyword">true</span>, <span class="keywordtype">double</span> normalisation = 1, <span class="keywordtype">double</span> bias = 0)</div>
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno">   69</span>        {</div>
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno">   70</span>            <span class="keywordflow">if</span> (kernel.GetLength(0) % 2 != 1 || kernel.GetLength(1) % 2 != 1)</div>
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno">   71</span>            {</div>
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno">   72</span>                <span class="keywordflow">throw</span> <span class="keyword">new</span> ArgumentException(<span class="stringliteral">&quot;The kernel must have an odd number of rows and columns!&quot;</span>, nameof(kernel));</div>
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno">   73</span>            }</div>
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno">   74</span> </div>
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno">   75</span>            this.Kernel = kernel;</div>
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno">   76</span> </div>
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno">   77</span>            <span class="keywordtype">int</span> kernelWidth = (this.<a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>.GetLength(0) - 1) / 2;</div>
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno">   78</span>            <span class="keywordtype">int</span> kernelHeight = (this.<a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>.GetLength(1) - 1) / 2;</div>
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno">   79</span> </div>
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno">   80</span>            this.TopLeftMargin = <span class="keyword">new</span> <a class="code hl_struct" href="struct_vect_sharp_1_1_point.html">Point</a>(kernelWidth * scale, kernelHeight * scale);</div>
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno">   81</span>            this.BottomRightMargin = <span class="keyword">new</span> <a class="code hl_struct" href="struct_vect_sharp_1_1_point.html">Point</a>(kernelWidth * scale, kernelHeight * scale);</div>
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno">   82</span>            this.Scale = scale;</div>
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno">   83</span>            this.PreserveAlpha = preserveAlpha;</div>
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno">   84</span>            this.Normalisation = normalisation;</div>
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno">   85</span>            this.Bias = bias;</div>
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno">   86</span>        }</div>
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno">   87</span><span class="comment"></span> </div>
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno">   88</span><span class="comment">        /// &lt;inheritdoc/&gt;</span></div>
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno">   89</span><span class="comment"></span>        [Pure]</div>
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno"><a class="line" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a45c5f133d8c3c1a976c9eeb3e1c8178d">   90</a></span>        <span class="keyword">public</span> <span class="keyword">virtual</span> <a class="code hl_class" href="class_vect_sharp_1_1_raster_image.html">RasterImage</a> <a class="code hl_function" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a45c5f133d8c3c1a976c9eeb3e1c8178d">Filter</a>(<a class="code hl_class" href="class_vect_sharp_1_1_raster_image.html">RasterImage</a> image, <span class="keywordtype">double</span> scale)</div>
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno">   91</span>        {</div>
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno">   92</span>            IntPtr tbrData = System.Runtime.InteropServices.Marshal.AllocHGlobal(image.<a class="code hl_property" href="class_vect_sharp_1_1_raster_image.html#a5c022bcd18b4e37c26df5ec67c8c2b71">Width</a> * image.<a class="code hl_property" href="class_vect_sharp_1_1_raster_image.html#a7fdcc792321aae93369d85c280bf696c">Height</a> * (image.<a class="code hl_property" href="class_vect_sharp_1_1_raster_image.html#a3012ff06029d327b3a280260fb2207f2">HasAlpha</a> ? 4 : 3));</div>
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno">   93</span> </div>
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno">   94</span>            <span class="keywordtype">int</span> width = image.<a class="code hl_property" href="class_vect_sharp_1_1_raster_image.html#a5c022bcd18b4e37c26df5ec67c8c2b71">Width</a>;</div>
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno">   95</span>            <span class="keywordtype">int</span> height = image.<a class="code hl_property" href="class_vect_sharp_1_1_raster_image.html#a7fdcc792321aae93369d85c280bf696c">Height</a>;</div>
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno">   96</span> </div>
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno">   97</span>            <span class="keywordtype">int</span> kernelWidth = (this.<a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>.GetLength(0) - 1) / 2;</div>
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno">   98</span>            <span class="keywordtype">int</span> kernelHeight = (this.<a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>.GetLength(1) - 1) / 2;</div>
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno">   99</span> </div>
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno">  100</span>            <span class="keywordtype">int</span> actualKernelWidth = (int)Math.Round(kernelWidth * scale * <span class="keyword">this</span>.Scale);</div>
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno">  101</span>            <span class="keywordtype">int</span> actualKernelHeight = (int)Math.Round(kernelHeight * scale * <span class="keyword">this</span>.Scale);</div>
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno">  102</span> </div>
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno">  103</span>            actualKernelWidth = Math.Max(actualKernelWidth, 1);</div>
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno">  104</span>            actualKernelHeight = Math.Max(actualKernelHeight, 1);</div>
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno">  105</span> </div>
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno">  106</span>            <span class="keywordtype">int</span>[] kernelX = <span class="keyword">new</span> <span class="keywordtype">int</span>[actualKernelWidth * 2 + 1];</div>
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno">  107</span> </div>
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno">  108</span>            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> x = 0; x &lt; actualKernelWidth * 2 + 1; x++)</div>
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno">  109</span>            {</div>
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno">  110</span>                kernelX[x] = (int)Math.Round((<span class="keywordtype">double</span>)(x - actualKernelWidth) / actualKernelWidth * kernelWidth + kernelWidth);</div>
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno">  111</span>            }</div>
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno">  112</span> </div>
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno">  113</span>            <span class="keywordtype">int</span>[] kernelY = <span class="keyword">new</span> <span class="keywordtype">int</span>[actualKernelHeight * 2 + 1];</div>
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno">  114</span> </div>
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno">  115</span>            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> y = 0; y &lt; actualKernelHeight * 2 + 1; y++)</div>
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno">  116</span>            {</div>
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno">  117</span>                kernelY[y] = (int)Math.Round((<span class="keywordtype">double</span>)(y - actualKernelHeight) / actualKernelHeight * kernelHeight + kernelHeight);</div>
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno">  118</span>            }</div>
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno">  119</span> </div>
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno">  120</span>            <span class="keywordtype">int</span>[] countsX = <span class="keyword">new</span> <span class="keywordtype">int</span>[2 * kernelWidth + 1];</div>
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno">  121</span> </div>
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno">  122</span>            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; 2 * actualKernelWidth + 1; i++)</div>
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno">  123</span>            {</div>
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno">  124</span>                countsX[kernelX[i]]++;</div>
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno">  125</span>            }</div>
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno">  126</span> </div>
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno">  127</span>            <span class="keywordtype">int</span>[] countsY = <span class="keyword">new</span> <span class="keywordtype">int</span>[2 * kernelHeight + 1];</div>
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno">  128</span> </div>
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno">  129</span>            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; 2 * actualKernelHeight + 1; i++)</div>
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno">  130</span>            {</div>
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno">  131</span>                countsY[kernelY[i]]++;</div>
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno">  132</span>            }</div>
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno">  133</span> </div>
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno">  134</span> </div>
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno">  135</span>            <span class="keywordtype">double</span>[] weightsX = <span class="keyword">new</span> <span class="keywordtype">double</span>[2 * actualKernelWidth + 1];</div>
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno">  136</span> </div>
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno">  137</span>            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; 2 * actualKernelWidth + 1; i++)</div>
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno">  138</span>            {</div>
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno">  139</span>                weightsX[i] = 1.0 / countsX[kernelX[i]];</div>
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno">  140</span>            }</div>
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno">  141</span> </div>
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno">  142</span>            <span class="keywordtype">double</span>[] weightsY = <span class="keyword">new</span> <span class="keywordtype">double</span>[2 * actualKernelHeight + 1];</div>
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno">  143</span> </div>
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno">  144</span>            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; 2 * actualKernelHeight + 1; i++)</div>
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno">  145</span>            {</div>
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno">  146</span>                weightsY[i] = 1.0 / countsY[kernelY[i]];</div>
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno">  147</span>            }</div>
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno">  148</span> </div>
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno">  149</span>            kernelWidth = actualKernelWidth;</div>
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno">  150</span>            kernelHeight = actualKernelHeight;</div>
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno">  151</span> </div>
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno">  152</span>            <span class="keywordtype">double</span> normalisation = this.<a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a4f2be240a6de3ec430e6b47cb22c3a31">Normalisation</a>;</div>
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno">  153</span> </div>
<div class="line"><a id="l00154" name="l00154"></a><span class="lineno">  154</span>            <span class="keywordflow">if</span> (<span class="keywordtype">double</span>.IsNaN(normalisation) || normalisation == 0)</div>
<div class="line"><a id="l00155" name="l00155"></a><span class="lineno">  155</span>            {</div>
<div class="line"><a id="l00156" name="l00156"></a><span class="lineno">  156</span>                normalisation = 1;</div>
<div class="line"><a id="l00157" name="l00157"></a><span class="lineno">  157</span>            }</div>
<div class="line"><a id="l00158" name="l00158"></a><span class="lineno">  158</span> </div>
<div class="line"><a id="l00159" name="l00159"></a><span class="lineno">  159</span>            <span class="keywordtype">double</span> totalWeight = 0;</div>
<div class="line"><a id="l00160" name="l00160"></a><span class="lineno">  160</span>            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; kernelWidth * 2 + 1; i++)</div>
<div class="line"><a id="l00161" name="l00161"></a><span class="lineno">  161</span>            {</div>
<div class="line"><a id="l00162" name="l00162"></a><span class="lineno">  162</span>                <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kernelHeight * 2 + 1; j++)</div>
<div class="line"><a id="l00163" name="l00163"></a><span class="lineno">  163</span>                {</div>
<div class="line"><a id="l00164" name="l00164"></a><span class="lineno">  164</span>                    totalWeight += <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>[kernelX[i], kernelY[j]] * weightsX[i] * weightsY[j];</div>
<div class="line"><a id="l00165" name="l00165"></a><span class="lineno">  165</span>                }</div>
<div class="line"><a id="l00166" name="l00166"></a><span class="lineno">  166</span>            }</div>
<div class="line"><a id="l00167" name="l00167"></a><span class="lineno">  167</span> </div>
<div class="line"><a id="l00168" name="l00168"></a><span class="lineno">  168</span>            <span class="keywordflow">if</span> (Math.Abs(totalWeight) &lt; 1e-5)</div>
<div class="line"><a id="l00169" name="l00169"></a><span class="lineno">  169</span>            {</div>
<div class="line"><a id="l00170" name="l00170"></a><span class="lineno">  170</span>                totalWeight = 1;</div>
<div class="line"><a id="l00171" name="l00171"></a><span class="lineno">  171</span>            }</div>
<div class="line"><a id="l00172" name="l00172"></a><span class="lineno">  172</span> </div>
<div class="line"><a id="l00173" name="l00173"></a><span class="lineno">  173</span> </div>
<div class="line"><a id="l00174" name="l00174"></a><span class="lineno">  174</span>            <span class="keywordtype">double</span> bias = this.Bias * 255;</div>
<div class="line"><a id="l00175" name="l00175"></a><span class="lineno">  175</span>            <span class="keywordtype">int</span> pixelSize = image.HasAlpha ? 4 : 3;</div>
<div class="line"><a id="l00176" name="l00176"></a><span class="lineno">  176</span>            <span class="keywordtype">int</span> stride = image.Width * pixelSize;</div>
<div class="line"><a id="l00177" name="l00177"></a><span class="lineno">  177</span> </div>
<div class="line"><a id="l00178" name="l00178"></a><span class="lineno">  178</span>            <span class="keywordtype">int</span> threads = Math.Min(8, Environment.ProcessorCount);</div>
<div class="line"><a id="l00179" name="l00179"></a><span class="lineno">  179</span> </div>
<div class="line"><a id="l00180" name="l00180"></a><span class="lineno">  180</span>            unsafe</div>
<div class="line"><a id="l00181" name="l00181"></a><span class="lineno">  181</span>            {</div>
<div class="line"><a id="l00182" name="l00182"></a><span class="lineno">  182</span>                <span class="keywordtype">byte</span>* input = (<span class="keywordtype">byte</span>*)image.<a class="code hl_property" href="class_vect_sharp_1_1_raster_image.html#aaa0c2c00b3f570797d0eb31ea899dae2">ImageDataAddress</a>;</div>
<div class="line"><a id="l00183" name="l00183"></a><span class="lineno">  183</span>                <span class="keywordtype">byte</span>* output = (<span class="keywordtype">byte</span>*)tbrData;</div>
<div class="line"><a id="l00184" name="l00184"></a><span class="lineno">  184</span> </div>
<div class="line"><a id="l00185" name="l00185"></a><span class="lineno">  185</span>                Action&lt;int&gt; yLoop;</div>
<div class="line"><a id="l00186" name="l00186"></a><span class="lineno">  186</span> </div>
<div class="line"><a id="l00187" name="l00187"></a><span class="lineno">  187</span>                <span class="keywordflow">if</span> (image.<a class="code hl_property" href="class_vect_sharp_1_1_raster_image.html#a3012ff06029d327b3a280260fb2207f2">HasAlpha</a> &amp;&amp; !<a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#ab32f045d8dfdef1dd0dc1647ef4eac99">PreserveAlpha</a>)</div>
<div class="line"><a id="l00188" name="l00188"></a><span class="lineno">  188</span>                {</div>
<div class="line"><a id="l00189" name="l00189"></a><span class="lineno">  189</span>                    yLoop = (y) =&gt;</div>
<div class="line"><a id="l00190" name="l00190"></a><span class="lineno">  190</span>                    {</div>
<div class="line"><a id="l00191" name="l00191"></a><span class="lineno">  191</span>                        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> x = 0; x &lt; width; x++)</div>
<div class="line"><a id="l00192" name="l00192"></a><span class="lineno">  192</span>                        {</div>
<div class="line"><a id="l00193" name="l00193"></a><span class="lineno">  193</span>                            <span class="keywordtype">double</span> R = 0;</div>
<div class="line"><a id="l00194" name="l00194"></a><span class="lineno">  194</span>                            <span class="keywordtype">double</span> G = 0;</div>
<div class="line"><a id="l00195" name="l00195"></a><span class="lineno">  195</span>                            <span class="keywordtype">double</span> B = 0;</div>
<div class="line"><a id="l00196" name="l00196"></a><span class="lineno">  196</span> </div>
<div class="line"><a id="l00197" name="l00197"></a><span class="lineno">  197</span>                            <span class="keywordtype">double</span> weight = 0;</div>
<div class="line"><a id="l00198" name="l00198"></a><span class="lineno">  198</span> </div>
<div class="line"><a id="l00199" name="l00199"></a><span class="lineno">  199</span>                            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> targetX = 0; targetX &lt;= kernelWidth * 2; targetX++)</div>
<div class="line"><a id="l00200" name="l00200"></a><span class="lineno">  200</span>                            {</div>
<div class="line"><a id="l00201" name="l00201"></a><span class="lineno">  201</span>                                <span class="keywordflow">for</span> (<span class="keywordtype">int</span> targetY = 0; targetY &lt;= kernelHeight * 2; targetY++)</div>
<div class="line"><a id="l00202" name="l00202"></a><span class="lineno">  202</span>                                {</div>
<div class="line"><a id="l00203" name="l00203"></a><span class="lineno">  203</span>                                    <span class="keywordtype">int</span> tX = Math.Min(Math.Max(0, x + targetX - kernelWidth), width - 1);</div>
<div class="line"><a id="l00204" name="l00204"></a><span class="lineno">  204</span>                                    <span class="keywordtype">int</span> tY = Math.Min(Math.Max(0, y + targetY - kernelHeight), height - 1);</div>
<div class="line"><a id="l00205" name="l00205"></a><span class="lineno">  205</span> </div>
<div class="line"><a id="l00206" name="l00206"></a><span class="lineno">  206</span>                                    <span class="keywordtype">double</span> a = input[tY * stride + tX * 4 + 3] / 255.0 * weightsX[targetX] * weightsY[targetY];</div>
<div class="line"><a id="l00207" name="l00207"></a><span class="lineno">  207</span> </div>
<div class="line"><a id="l00208" name="l00208"></a><span class="lineno">  208</span>                                    <span class="keywordtype">int</span> projectedX = kernelX[targetX];</div>
<div class="line"><a id="l00209" name="l00209"></a><span class="lineno">  209</span>                                    <span class="keywordtype">int</span> projectedY = kernelY[targetY];</div>
<div class="line"><a id="l00210" name="l00210"></a><span class="lineno">  210</span> </div>
<div class="line"><a id="l00211" name="l00211"></a><span class="lineno">  211</span>                                    weight += <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>[projectedX, projectedY] * a;</div>
<div class="line"><a id="l00212" name="l00212"></a><span class="lineno">  212</span> </div>
<div class="line"><a id="l00213" name="l00213"></a><span class="lineno">  213</span>                                    R += <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>[projectedX, projectedY] * input[tY * stride + tX * 4] * a;</div>
<div class="line"><a id="l00214" name="l00214"></a><span class="lineno">  214</span>                                    G += <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>[projectedX, projectedY] * input[tY * stride + tX * 4 + 1] * a;</div>
<div class="line"><a id="l00215" name="l00215"></a><span class="lineno">  215</span>                                    B += <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>[projectedX, projectedY] * input[tY * stride + tX * 4 + 2] * a;</div>
<div class="line"><a id="l00216" name="l00216"></a><span class="lineno">  216</span>                                }</div>
<div class="line"><a id="l00217" name="l00217"></a><span class="lineno">  217</span>                            }</div>
<div class="line"><a id="l00218" name="l00218"></a><span class="lineno">  218</span> </div>
<div class="line"><a id="l00219" name="l00219"></a><span class="lineno">  219</span>                            <span class="keywordflow">if</span> (weight != 0)</div>
<div class="line"><a id="l00220" name="l00220"></a><span class="lineno">  220</span>                            {</div>
<div class="line"><a id="l00221" name="l00221"></a><span class="lineno">  221</span>                                output[y * stride + x * 4] = (byte)Math.Min(255, Math.Max(0, R / (normalisation * weight) + bias));</div>
<div class="line"><a id="l00222" name="l00222"></a><span class="lineno">  222</span>                                output[y * stride + x * 4 + 1] = (byte)Math.Min(255, Math.Max(0, G / (normalisation * weight) + bias));</div>
<div class="line"><a id="l00223" name="l00223"></a><span class="lineno">  223</span>                                output[y * stride + x * 4 + 2] = (byte)Math.Min(255, Math.Max(0, B / (normalisation * weight) + bias));</div>
<div class="line"><a id="l00224" name="l00224"></a><span class="lineno">  224</span>                                output[y * stride + x * 4 + 3] = (byte)Math.Min(255, Math.Max(0, (weight / (normalisation * totalWeight) * 255 + bias)));</div>
<div class="line"><a id="l00225" name="l00225"></a><span class="lineno">  225</span>                            }</div>
<div class="line"><a id="l00226" name="l00226"></a><span class="lineno">  226</span>                            <span class="keywordflow">else</span></div>
<div class="line"><a id="l00227" name="l00227"></a><span class="lineno">  227</span>                            {</div>
<div class="line"><a id="l00228" name="l00228"></a><span class="lineno">  228</span>                                output[y * stride + x * 4] = 0;</div>
<div class="line"><a id="l00229" name="l00229"></a><span class="lineno">  229</span>                                output[y * stride + x * 4 + 1] = 0;</div>
<div class="line"><a id="l00230" name="l00230"></a><span class="lineno">  230</span>                                output[y * stride + x * 4 + 2] = 0;</div>
<div class="line"><a id="l00231" name="l00231"></a><span class="lineno">  231</span>                                output[y * stride + x * 4 + 3] = 0;</div>
<div class="line"><a id="l00232" name="l00232"></a><span class="lineno">  232</span>                            }</div>
<div class="line"><a id="l00233" name="l00233"></a><span class="lineno">  233</span>                        }</div>
<div class="line"><a id="l00234" name="l00234"></a><span class="lineno">  234</span>                    };</div>
<div class="line"><a id="l00235" name="l00235"></a><span class="lineno">  235</span>                }</div>
<div class="line"><a id="l00236" name="l00236"></a><span class="lineno">  236</span>                <span class="keywordflow">else</span> <span class="keywordflow">if</span> (image.<a class="code hl_property" href="class_vect_sharp_1_1_raster_image.html#a3012ff06029d327b3a280260fb2207f2">HasAlpha</a> &amp;&amp; <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#ab32f045d8dfdef1dd0dc1647ef4eac99">PreserveAlpha</a>)</div>
<div class="line"><a id="l00237" name="l00237"></a><span class="lineno">  237</span>                {</div>
<div class="line"><a id="l00238" name="l00238"></a><span class="lineno">  238</span>                    yLoop = (y) =&gt;</div>
<div class="line"><a id="l00239" name="l00239"></a><span class="lineno">  239</span>                    {</div>
<div class="line"><a id="l00240" name="l00240"></a><span class="lineno">  240</span>                        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> x = 0; x &lt; width; x++)</div>
<div class="line"><a id="l00241" name="l00241"></a><span class="lineno">  241</span>                        {</div>
<div class="line"><a id="l00242" name="l00242"></a><span class="lineno">  242</span>                            <span class="keywordtype">double</span> R = 0;</div>
<div class="line"><a id="l00243" name="l00243"></a><span class="lineno">  243</span>                            <span class="keywordtype">double</span> G = 0;</div>
<div class="line"><a id="l00244" name="l00244"></a><span class="lineno">  244</span>                            <span class="keywordtype">double</span> B = 0;</div>
<div class="line"><a id="l00245" name="l00245"></a><span class="lineno">  245</span> </div>
<div class="line"><a id="l00246" name="l00246"></a><span class="lineno">  246</span>                            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> targetX = 0; targetX &lt;= kernelWidth * 2; targetX++)</div>
<div class="line"><a id="l00247" name="l00247"></a><span class="lineno">  247</span>                            {</div>
<div class="line"><a id="l00248" name="l00248"></a><span class="lineno">  248</span>                                <span class="keywordflow">for</span> (<span class="keywordtype">int</span> targetY = 0; targetY &lt;= kernelHeight * 2; targetY++)</div>
<div class="line"><a id="l00249" name="l00249"></a><span class="lineno">  249</span>                                {</div>
<div class="line"><a id="l00250" name="l00250"></a><span class="lineno">  250</span>                                    <span class="keywordtype">int</span> tX = Math.Min(Math.Max(0, x + targetX - kernelWidth), width - 1);</div>
<div class="line"><a id="l00251" name="l00251"></a><span class="lineno">  251</span>                                    <span class="keywordtype">int</span> tY = Math.Min(Math.Max(0, y + targetY - kernelHeight), height - 1);</div>
<div class="line"><a id="l00252" name="l00252"></a><span class="lineno">  252</span> </div>
<div class="line"><a id="l00253" name="l00253"></a><span class="lineno">  253</span>                                    <span class="keywordtype">int</span> projectedX = kernelX[targetX];</div>
<div class="line"><a id="l00254" name="l00254"></a><span class="lineno">  254</span>                                    <span class="keywordtype">int</span> projectedY = kernelY[targetY];</div>
<div class="line"><a id="l00255" name="l00255"></a><span class="lineno">  255</span> </div>
<div class="line"><a id="l00256" name="l00256"></a><span class="lineno">  256</span>                                    R += <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>[projectedX, projectedY] * input[tY * stride + tX * 4] * weightsX[targetX] * weightsY[targetY];</div>
<div class="line"><a id="l00257" name="l00257"></a><span class="lineno">  257</span>                                    G += <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>[projectedX, projectedY] * input[tY * stride + tX * 4 + 1] * weightsX[targetX] * weightsY[targetY];</div>
<div class="line"><a id="l00258" name="l00258"></a><span class="lineno">  258</span>                                    B += <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>[projectedX, projectedY] * input[tY * stride + tX * 4 + 2] * weightsX[targetX] * weightsY[targetY];</div>
<div class="line"><a id="l00259" name="l00259"></a><span class="lineno">  259</span>                                }</div>
<div class="line"><a id="l00260" name="l00260"></a><span class="lineno">  260</span>                            }</div>
<div class="line"><a id="l00261" name="l00261"></a><span class="lineno">  261</span> </div>
<div class="line"><a id="l00262" name="l00262"></a><span class="lineno">  262</span>                            output[y * stride + x * 4] = (byte)Math.Min(255, Math.Max(0, R / (normalisation * totalWeight) + bias));</div>
<div class="line"><a id="l00263" name="l00263"></a><span class="lineno">  263</span>                            output[y * stride + x * 4 + 1] = (byte)Math.Min(255, Math.Max(0, G / (normalisation * totalWeight) + bias));</div>
<div class="line"><a id="l00264" name="l00264"></a><span class="lineno">  264</span>                            output[y * stride + x * 4 + 2] = (byte)Math.Min(255, Math.Max(0, B / (normalisation * totalWeight) + bias));</div>
<div class="line"><a id="l00265" name="l00265"></a><span class="lineno">  265</span>                            output[y * stride + x * 4 + 3] = input[y * stride + x * 4 + 3];</div>
<div class="line"><a id="l00266" name="l00266"></a><span class="lineno">  266</span>                        }</div>
<div class="line"><a id="l00267" name="l00267"></a><span class="lineno">  267</span>                    };</div>
<div class="line"><a id="l00268" name="l00268"></a><span class="lineno">  268</span>                }</div>
<div class="line"><a id="l00269" name="l00269"></a><span class="lineno">  269</span>                <span class="keywordflow">else</span></div>
<div class="line"><a id="l00270" name="l00270"></a><span class="lineno">  270</span>                {</div>
<div class="line"><a id="l00271" name="l00271"></a><span class="lineno">  271</span>                    yLoop = (y) =&gt;</div>
<div class="line"><a id="l00272" name="l00272"></a><span class="lineno">  272</span>                    {</div>
<div class="line"><a id="l00273" name="l00273"></a><span class="lineno">  273</span>                        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> x = 0; x &lt; width; x++)</div>
<div class="line"><a id="l00274" name="l00274"></a><span class="lineno">  274</span>                        {</div>
<div class="line"><a id="l00275" name="l00275"></a><span class="lineno">  275</span>                            <span class="keywordtype">double</span> R = 0;</div>
<div class="line"><a id="l00276" name="l00276"></a><span class="lineno">  276</span>                            <span class="keywordtype">double</span> G = 0;</div>
<div class="line"><a id="l00277" name="l00277"></a><span class="lineno">  277</span>                            <span class="keywordtype">double</span> B = 0;</div>
<div class="line"><a id="l00278" name="l00278"></a><span class="lineno">  278</span> </div>
<div class="line"><a id="l00279" name="l00279"></a><span class="lineno">  279</span>                            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> targetX = 0; targetX &lt;= kernelWidth * 2; targetX++)</div>
<div class="line"><a id="l00280" name="l00280"></a><span class="lineno">  280</span>                            {</div>
<div class="line"><a id="l00281" name="l00281"></a><span class="lineno">  281</span>                                <span class="keywordflow">for</span> (<span class="keywordtype">int</span> targetY = 0; targetY &lt;= kernelHeight * 2; targetY++)</div>
<div class="line"><a id="l00282" name="l00282"></a><span class="lineno">  282</span>                                {</div>
<div class="line"><a id="l00283" name="l00283"></a><span class="lineno">  283</span>                                    <span class="keywordtype">int</span> tX = Math.Min(Math.Max(0, x + targetX - kernelWidth), width - 1);</div>
<div class="line"><a id="l00284" name="l00284"></a><span class="lineno">  284</span>                                    <span class="keywordtype">int</span> tY = Math.Min(Math.Max(0, y + targetY - kernelHeight), height - 1);</div>
<div class="line"><a id="l00285" name="l00285"></a><span class="lineno">  285</span> </div>
<div class="line"><a id="l00286" name="l00286"></a><span class="lineno">  286</span>                                    <span class="keywordtype">int</span> projectedX = kernelX[targetX];</div>
<div class="line"><a id="l00287" name="l00287"></a><span class="lineno">  287</span>                                    <span class="keywordtype">int</span> projectedY = kernelY[targetY];</div>
<div class="line"><a id="l00288" name="l00288"></a><span class="lineno">  288</span> </div>
<div class="line"><a id="l00289" name="l00289"></a><span class="lineno">  289</span>                                    R += <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>[projectedX, projectedY] * input[tY * stride + tX * 3] * weightsX[targetX] * weightsY[targetY];</div>
<div class="line"><a id="l00290" name="l00290"></a><span class="lineno">  290</span>                                    G += <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>[projectedX, projectedY] * input[tY * stride + tX * 3 + 1] * weightsX[targetX] * weightsY[targetY];</div>
<div class="line"><a id="l00291" name="l00291"></a><span class="lineno">  291</span>                                    B += <a class="code hl_property" href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">Kernel</a>[projectedX, projectedY] * input[tY * stride + tX * 3 + 2] * weightsX[targetX] * weightsY[targetY];</div>
<div class="line"><a id="l00292" name="l00292"></a><span class="lineno">  292</span>                                }</div>
<div class="line"><a id="l00293" name="l00293"></a><span class="lineno">  293</span>                            }</div>
<div class="line"><a id="l00294" name="l00294"></a><span class="lineno">  294</span> </div>
<div class="line"><a id="l00295" name="l00295"></a><span class="lineno">  295</span>                            output[y * stride + x * 3] = (byte)Math.Min(255, Math.Max(0, R / (normalisation * totalWeight) + bias));</div>
<div class="line"><a id="l00296" name="l00296"></a><span class="lineno">  296</span>                            output[y * stride + x * 3 + 1] = (byte)Math.Min(255, Math.Max(0, G / (normalisation * totalWeight) + bias));</div>
<div class="line"><a id="l00297" name="l00297"></a><span class="lineno">  297</span>                            output[y * stride + x * 3 + 2] = (byte)Math.Min(255, Math.Max(0, B / (normalisation * totalWeight) + bias));</div>
<div class="line"><a id="l00298" name="l00298"></a><span class="lineno">  298</span>                        }</div>
<div class="line"><a id="l00299" name="l00299"></a><span class="lineno">  299</span>                    };</div>
<div class="line"><a id="l00300" name="l00300"></a><span class="lineno">  300</span>                }</div>
<div class="line"><a id="l00301" name="l00301"></a><span class="lineno">  301</span> </div>
<div class="line"><a id="l00302" name="l00302"></a><span class="lineno">  302</span>                <span class="keywordflow">if</span> (threads == 1)</div>
<div class="line"><a id="l00303" name="l00303"></a><span class="lineno">  303</span>                {</div>
<div class="line"><a id="l00304" name="l00304"></a><span class="lineno">  304</span>                    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> y = 0; y &lt; height; y++)</div>
<div class="line"><a id="l00305" name="l00305"></a><span class="lineno">  305</span>                    {</div>
<div class="line"><a id="l00306" name="l00306"></a><span class="lineno">  306</span>                        yLoop(y);</div>
<div class="line"><a id="l00307" name="l00307"></a><span class="lineno">  307</span>                    }</div>
<div class="line"><a id="l00308" name="l00308"></a><span class="lineno">  308</span>                }</div>
<div class="line"><a id="l00309" name="l00309"></a><span class="lineno">  309</span>                <span class="keywordflow">else</span></div>
<div class="line"><a id="l00310" name="l00310"></a><span class="lineno">  310</span>                {</div>
<div class="line"><a id="l00311" name="l00311"></a><span class="lineno">  311</span>                    ParallelOptions options = <span class="keyword">new</span> ParallelOptions() { MaxDegreeOfParallelism = threads };</div>
<div class="line"><a id="l00312" name="l00312"></a><span class="lineno">  312</span> </div>
<div class="line"><a id="l00313" name="l00313"></a><span class="lineno">  313</span>                    Parallel.For(0, height, options, yLoop);</div>
<div class="line"><a id="l00314" name="l00314"></a><span class="lineno">  314</span>                }</div>
<div class="line"><a id="l00315" name="l00315"></a><span class="lineno">  315</span>            }</div>
<div class="line"><a id="l00316" name="l00316"></a><span class="lineno">  316</span> </div>
<div class="line"><a id="l00317" name="l00317"></a><span class="lineno">  317</span>            <span class="keywordflow">return</span> <span class="keyword">new</span> <a class="code hl_class" href="class_vect_sharp_1_1_raster_image.html">RasterImage</a>(tbrData, image.<a class="code hl_property" href="class_vect_sharp_1_1_raster_image.html#a5c022bcd18b4e37c26df5ec67c8c2b71">Width</a>, image.<a class="code hl_property" href="class_vect_sharp_1_1_raster_image.html#a7fdcc792321aae93369d85c280bf696c">Height</a>, image.<a class="code hl_property" href="class_vect_sharp_1_1_raster_image.html#a3012ff06029d327b3a280260fb2207f2">HasAlpha</a>, image.<a class="code hl_property" href="class_vect_sharp_1_1_raster_image.html#a5a5e8f5228b8aa3aa103693265fa900e">Interpolate</a>);</div>
<div class="line"><a id="l00318" name="l00318"></a><span class="lineno">  318</span>        }</div>
<div class="line"><a id="l00319" name="l00319"></a><span class="lineno">  319</span>    }</div>
<div class="line"><a id="l00320" name="l00320"></a><span class="lineno">  320</span>}</div>
<div class="ttc" id="aclass_vect_sharp_1_1_filters_1_1_convolution_filter_html"><div class="ttname"><a href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html">VectSharp.Filters.ConvolutionFilter</a></div><div class="ttdoc">Represents a filter that applies a matrix convolution to the image.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_filter_8cs_source.html#l00027">ConvolutionFilter.cs:28</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_filters_1_1_convolution_filter_html_a32d973bf7389f4ac07d68ca9cf2a4dbc"><div class="ttname"><a href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a32d973bf7389f4ac07d68ca9cf2a4dbc">VectSharp.Filters.ConvolutionFilter.TopLeftMargin</a></div><div class="ttdeci">Point TopLeftMargin</div><div class="ttdoc">Determines how much the area of the filter's subject should be expanded on the top-left to accommodat...</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_filter_8cs_source.html#l00030">ConvolutionFilter.cs:30</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_filters_1_1_convolution_filter_html_a45c5f133d8c3c1a976c9eeb3e1c8178d"><div class="ttname"><a href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a45c5f133d8c3c1a976c9eeb3e1c8178d">VectSharp.Filters.ConvolutionFilter.Filter</a></div><div class="ttdeci">virtual RasterImage Filter(RasterImage image, double scale)</div><div class="ttdoc">Applies the filter to a RasterImage. A new RasterImage containing the filtered image....</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_filter_8cs_source.html#l00090">ConvolutionFilter.cs:90</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_filters_1_1_convolution_filter_html_a4f2be240a6de3ec430e6b47cb22c3a31"><div class="ttname"><a href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a4f2be240a6de3ec430e6b47cb22c3a31">VectSharp.Filters.ConvolutionFilter.Normalisation</a></div><div class="ttdeci">virtual double Normalisation</div><div class="ttdoc">The normalisation value that is applies to the kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_filter_8cs_source.html#l00042">ConvolutionFilter.cs:42</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_filters_1_1_convolution_filter_html_a73b327812cc43052706a859db30ad9cd"><div class="ttname"><a href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a73b327812cc43052706a859db30ad9cd">VectSharp.Filters.ConvolutionFilter.ConvolutionFilter</a></div><div class="ttdeci">ConvolutionFilter(double[,] kernel, double scale, bool preserveAlpha=true, double normalisation=1, double bias=0)</div><div class="ttdoc">Creates a new ConvolutionFilter with the specified parameters.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_filter_8cs_source.html#l00068">ConvolutionFilter.cs:68</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_filters_1_1_convolution_filter_html_a8328d79387cab9e761d82eb5b63425db"><div class="ttname"><a href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a8328d79387cab9e761d82eb5b63425db">VectSharp.Filters.ConvolutionFilter.Scale</a></div><div class="ttdeci">virtual double Scale</div><div class="ttdoc">The scale relating the size of the kernel to graphics units.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_filter_8cs_source.html#l00052">ConvolutionFilter.cs:52</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_filters_1_1_convolution_filter_html_a84aa7dae990d0e74ec7403304fbbb298"><div class="ttname"><a href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a84aa7dae990d0e74ec7403304fbbb298">VectSharp.Filters.ConvolutionFilter.Kernel</a></div><div class="ttdeci">virtual double[,] Kernel</div><div class="ttdoc">The kernel of the ConvolutionFilter. The dimensions of this matrix should all be odd numbers....</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_filter_8cs_source.html#l00037">ConvolutionFilter.cs:37</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_filters_1_1_convolution_filter_html_a8c83462414bf7df2ae2d2a957dbfbfc8"><div class="ttname"><a href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#a8c83462414bf7df2ae2d2a957dbfbfc8">VectSharp.Filters.ConvolutionFilter.Bias</a></div><div class="ttdeci">virtual double Bias</div><div class="ttdoc">The bias value that is added to every colour component when the filter is applied.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_filter_8cs_source.html#l00047">ConvolutionFilter.cs:47</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_filters_1_1_convolution_filter_html_ab32f045d8dfdef1dd0dc1647ef4eac99"><div class="ttname"><a href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#ab32f045d8dfdef1dd0dc1647ef4eac99">VectSharp.Filters.ConvolutionFilter.PreserveAlpha</a></div><div class="ttdeci">virtual bool PreserveAlpha</div><div class="ttdoc">If this is true, the alpha value of the input pixels is preserved. Otherwise, the alpha channel is su...</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_filter_8cs_source.html#l00057">ConvolutionFilter.cs:57</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_filters_1_1_convolution_filter_html_ade808cf103a8c230dfa7d04440853b2b"><div class="ttname"><a href="class_vect_sharp_1_1_filters_1_1_convolution_filter.html#ade808cf103a8c230dfa7d04440853b2b">VectSharp.Filters.ConvolutionFilter.BottomRightMargin</a></div><div class="ttdeci">Point BottomRightMargin</div><div class="ttdoc">Determines how much the area of the filter's subject should be expanded on the bottom-right to accomm...</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_filter_8cs_source.html#l00032">ConvolutionFilter.cs:32</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_raster_image_html"><div class="ttname"><a href="class_vect_sharp_1_1_raster_image.html">VectSharp.RasterImage</a></div><div class="ttdoc">Represents a raster image, created from raw pixel data. Consider using the derived classes included i...</div><div class="ttdef"><b>Definition:</b> <a href="_raster_image_8cs_source.html#l00100">RasterImage.cs:101</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_raster_image_html_a3012ff06029d327b3a280260fb2207f2"><div class="ttname"><a href="class_vect_sharp_1_1_raster_image.html#a3012ff06029d327b3a280260fb2207f2">VectSharp.RasterImage.HasAlpha</a></div><div class="ttdeci">bool HasAlpha</div><div class="ttdoc">Determines whether the image has an alpha channel.</div><div class="ttdef"><b>Definition:</b> <a href="_raster_image_8cs_source.html#l00120">RasterImage.cs:120</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_raster_image_html_a5a5e8f5228b8aa3aa103693265fa900e"><div class="ttname"><a href="class_vect_sharp_1_1_raster_image.html#a5a5e8f5228b8aa3aa103693265fa900e">VectSharp.RasterImage.Interpolate</a></div><div class="ttdeci">bool Interpolate</div><div class="ttdoc">Determines whether the image should be interpolated when it is resized.</div><div class="ttdef"><b>Definition:</b> <a href="_raster_image_8cs_source.html#l00135">RasterImage.cs:135</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_raster_image_html_a5c022bcd18b4e37c26df5ec67c8c2b71"><div class="ttname"><a href="class_vect_sharp_1_1_raster_image.html#a5c022bcd18b4e37c26df5ec67c8c2b71">VectSharp.RasterImage.Width</a></div><div class="ttdeci">int Width</div><div class="ttdoc">The width in pixels of the image.</div><div class="ttdef"><b>Definition:</b> <a href="_raster_image_8cs_source.html#l00125">RasterImage.cs:125</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_raster_image_html_a7fdcc792321aae93369d85c280bf696c"><div class="ttname"><a href="class_vect_sharp_1_1_raster_image.html#a7fdcc792321aae93369d85c280bf696c">VectSharp.RasterImage.Height</a></div><div class="ttdeci">int Height</div><div class="ttdoc">The height in pixels of the image.</div><div class="ttdef"><b>Definition:</b> <a href="_raster_image_8cs_source.html#l00130">RasterImage.cs:130</a></div></div>
<div class="ttc" id="aclass_vect_sharp_1_1_raster_image_html_aaa0c2c00b3f570797d0eb31ea899dae2"><div class="ttname"><a href="class_vect_sharp_1_1_raster_image.html#aaa0c2c00b3f570797d0eb31ea899dae2">VectSharp.RasterImage.ImageDataAddress</a></div><div class="ttdeci">IntPtr ImageDataAddress</div><div class="ttdoc">The memory address of the image pixel data.</div><div class="ttdef"><b>Definition:</b> <a href="_raster_image_8cs_source.html#l00105">RasterImage.cs:105</a></div></div>
<div class="ttc" id="ainterface_vect_sharp_1_1_filters_1_1_i_location_invariant_filter_html"><div class="ttname"><a href="interface_vect_sharp_1_1_filters_1_1_i_location_invariant_filter.html">VectSharp.Filters.ILocationInvariantFilter</a></div><div class="ttdoc">Represents a filter that can be applied to an image regardless of its location on the graphics surfac...</div><div class="ttdef"><b>Definition:</b> <a href="_filters_8cs_source.html#l00042">Filters.cs:43</a></div></div>
<div class="ttc" id="anamespace_vect_sharp_1_1_filters_html"><div class="ttname"><a href="namespace_vect_sharp_1_1_filters.html">VectSharp.Filters</a></div><div class="ttdef"><b>Definition:</b> <a href="_box_blur_filter_8cs_source.html#l00022">BoxBlurFilter.cs:23</a></div></div>
<div class="ttc" id="astruct_vect_sharp_1_1_point_html"><div class="ttname"><a href="struct_vect_sharp_1_1_point.html">VectSharp.Point</a></div><div class="ttdoc">Represents a point relative to an origin in the top-left corner.</div><div class="ttdef"><b>Definition:</b> <a href="_point_8cs_source.html#l00031">Point.cs:32</a></div></div>
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